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在AOA无线定位中,需要测量特征测量值AOA。而在蜂窝网络的无线测量中,由于非视距传播和多径的影响,AOA测量值误差较大,从而定位精度较低。Kalman滤波技术是一种处理定位数据的有效手段,尤其是动态定位数据,它不仅利用当前的观测量,而且充分利用以前的观测数据,根据线性最小方差原理,求出最优估计。仿真结果表明,Kalman滤波技术可以有效抑制AOA测量误差。
In AOA wireless positioning, the characteristic measurement AOA needs to be measured. However, in the wireless measurement of cellular networks, the AOA measurement error is larger due to the effect of non-line-of-sight propagation and multipath, so that the positioning accuracy is low. Kalman filtering technique is an effective method to process the positioning data, especially the dynamic positioning data. It not only makes use of the current observation but also makes full use of the previous observation data to find the optimal estimation based on the principle of linear minimum variance. Simulation results show that Kalman filtering can effectively suppress AOA measurement error.